Organelle Aging Predicts Human Disease
- 1Stanford University
Abstract
Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-{varepsilon}4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience.
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BibTeX
@misc{ying2026organelle,
title = {{Organelle Aging Predicts Human Disease}},
author = {K. Ying and K. K. Roh and K. L. Chen and V. A. Bot and D. Y. Ding and A. Farinas and The Global Neurodegeneration Proteomics Consortium (GNPC) and C. Ma and H. S.-H. Oh and A. Isakova and T. Wyss-Coray},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.01.763400},
url = {https://www.biorxiv.org/content/10.64898/2026.11.01.763400v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Organelle Aging Predicts Human Disease
AU - K. Ying
AU - K. K. Roh
AU - K. L. Chen
AU - V. A. Bot
AU - D. Y. Ding
AU - A. Farinas
AU - The Global Neurodegeneration Proteomics Consortium (GNPC)
AU - C. Ma
AU - H. S.-H. Oh
AU - A. Isakova
AU - T. Wyss-Coray
PY - 2026
DA - 2026/11/01
PB - bioRxiv
DO - 10.64898/2026.11.01.763400
UR - https://www.biorxiv.org/content/10.64898/2026.11.01.763400v1
AB - Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-{varepsilon}4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience.
ER -